TLDR
- GPT stands for Generative Pre-trained Transformer — a family of AI models that generate human-like text by predicting what word comes next.
- Developed by OpenAI, but not exclusive to ChatGPT — the technology powers Copilot, Jasper, Notion AI, and many other tools.
- Name breakdown: Generative (creates new text), Pre-trained (learns language broadly from books and the internet before fine-tuning), Transformer (the neural network architecture Google introduced in 2017).
- Core capabilities: dialogue, writing articles or emails, summarization, translation, code generation, and analyzing unstructured data like screenshots.
- Model evolution: GPT-1 (117M parameters, 2018), GPT-2 (1.5B, 2019), GPT-3 (175B, 2020), GPT-4 (2023), GPT-4o and o1 (2024), GPT-4.5, GPT-4.1 and GPT-5 (2025), GPT-5.1 and GPT-5.2 (2026).
- GPT-5 is the current flagship. It merged the GPT-4 line and the “o” reasoning models into one model that decides on its own when to think longer for harder questions.
- Main alternatives: Claude Opus 4.7 (bigger context, very conversational), Gemini 3 Pro (strong at coding and multimodal), Llama 4 (open source), plus DeepSeek V3.2 and Qwen from China.
- Where to try it: Overchat AI (multi-model access), ChatGPT (free tier uses GPT-5 with limits), or OpenAI Playground for developers.
GPT (Generative Pre-trained Transformer) stands for a family of large language models that can generate text. Hence, the “Generative” in the name. This technology was developed by OpenAI, the company behind the ever popular chatbot ChatGPT. However, it is not exclusive to ChatGPT.
Let’s unpack it in detail.
What Is a GPT?
GPT is an AI model that has learned to understand and produce natural language. It was trained on vast amounts of text, taken from books, websites, and, which is why we call it “pre-trained,” and it uses a neural network architecture called a Transformer.
Because of this training, GPT can take in a prompt (some input text) and then continue or respond to it with new, coherent text that sounds like something a person might write.
Thanks to its training, GPT knows grammar, facts, and writing styles, which it uses to predict the next words in a sentence. In practice, this means GPT can:
- Write essays
- Generate code
- Summarize documents
- Translate from one language to another
- And more
Why We Call Them Generative Pre-trained Transformers?
We call these models generative because they create new text, not just categorize or identify existing text, like machine-learning models in the past did. Here’s what each word in the name means:
- Generative: because it generates new content. Unlike a classifier that labels text, a generative model creates text, for example, an article. As it does so, GPT doesn’t copy and paste sentences from its training data, but produces new ones by statistically predicting what comes next based on the patterns it learned.
- Pre-trained: because GPT models aren’t trained from scratch for each new task. They go through a massive pre-training phase, essentially reading the internet and books, to learn the general structure of language, during which the model acquires knowledge. This is why, unlike other technologies, GPT can perform tasks it wasn’t trained for. We call this zero-shot or few-shot learning. Essentially, it can improvise.
- Transformer: because Google isn’t very good at naming things clearly. Transformer is what we call the neural network architecture that GPT uses. It was introduced by Google researchers in 2017 in a paper titled “Attention Is All You Need”.
So, GPT itself is an abbreviation of 3 things: the ability to generate new text, the way these models are trained, and the architecture they’re built on.
This mix of characteristics differentiates new AI models from earlier RNN and LSTM models, and it’s why a GPT can read a paragraph and remember who’s doing what, or what you and the chatbot were talking about 15 messages ago, even as it writes new responses.
What Does GPT Do?
At their core, GPTs write. They receive some input prompt and respond to it coherently. Ideally, in a way a human would answer a question. This core skill translates into multiple applications:
- Carry on a dialogue, answer questions and chat
- Write paragraphs and even pages of text in different formats: emails, articles, essays
- Summarize long texts into shorter, bite-sized summaries
- Translate between languages
- Generating computer code in different programming languages
Tools like GitHub Copilot based on OpenAI's Codex, which is a GPT-3 derivative, are especially strong at this.
Last but not least, GPTs can analyze unstructured data. For example, you can take a screenshot of a Google Analytics report, send it to the chatbot and ask to find insights, and it will. GPT-5, GPT-5.1 and Claude Opus 4.7 can do it with about 95% accuracy.
How Was GPT Invented?
The first Generative Pre-trained Transformer was introduced in a 2018 paper by OpenAI titled “Improving Language Understanding by Generative Pre-Training.”
OpenAI took the Transformer architecture created by Google and applied it to a two-stage process:
- Train the model on a ton of data
- Manually fine tune it for specific tasks
In practice, OpenAI had an army of people, called AI trainers, go through thousands of AI answers and give them either a thumbs up or thumbs down, as well as some comments on what the model did right or wrong. This knowledge then was baked into the AI to help improve its accuracy.
The first GPT, GPT-1 had about 117 million parameters, which was groundbreaking at the time. The successor released in 2019, GPT-2, dramatically increased the size – ~1.5 billion parameters, over 10× over GPT-1.
This model could confidently write paragraphs of seemingly human writing. In fact, GPT-2 was so good at this that OpenAI initially withheld the full model because of misuse concerns.
The next generational leap happened in 2020, when OpenAI released GPT-3 with 175 billion parameters, two orders of magnitude larger than GPT-2. GPT-3 could handle tasks with few-shot learning – you could give a couple of examples in the prompt and it would infer the pattern and perform the task.
The next milestone was GPT-4, released in March 2023. Much of the details behind GPT-4 are kept secret, so we don’t know how many parameters it has — likely trillions. Notably, GPT-4 is multimodal, meaning it can accept images and audio as part of its input.
However, when it comes to reasoning ability many say that GPT 4 is a minor improvement over GPT 3, and that we’re hitting a plateau of diminishing returns, where scaling the model doesn’t produce a linear improvement in performance.
After GPT-4, OpenAI continued to refine the model, releasing GPT-4o in 2024, GPT-4.5 and GPT-4.1 in 2025, and then GPT-5 later that same year.
GPT-5 finally delivered on the promised “supermodel” idea — it combined the GPT-4 line and the “o” reasoning models into one system that decides on its own when to think longer for a harder question. OpenAI followed up with GPT-5.1 and, as of 2026, GPT-5.2, each iteration improving on factual accuracy, coding, and long-context handling.
Popular GPT Models
OpenAI has developed several versions and variants of GPT models over the years. Let’s look at some of the notable GPT-based models as of 2026, and what makes each unique:
GPT-5 (and GPT-5.1, GPT-5.2)
GPT-5 launched in 2025 as OpenAI’s first unified model that combines the GPT-4 line with the “o” reasoning models. Instead of asking users to pick between a fast model and a thinking model, GPT-5 routes simple prompts straight to a quick answer and harder ones into an internal chain-of-thought.
- Built-in reasoning — no separate “o” model to pick from
- Significantly fewer hallucinations than GPT-4 and GPT-4o
- Fully multimodal — text, images, audio, and video input
- Long context window (hundreds of thousands of tokens) suitable for entire codebases and books
OpenAI has since released GPT-5.1 and GPT-5.2 as iterative upgrades focused on coding, factual accuracy, and faster responses. GPT-5 is the default in ChatGPT for paid users; the free tier gets a lightweight version (GPT-5 mini) with daily message limits. You can also use the full GPT-5 family on Overchat AI without OpenAI subscription caps.
GPT-4.1
GPT-4.1, launched in April 2025, is a specialized model optimized for coding and handling extremely large inputs. OpenAI released it in three versions: GPT-4.1, 4.1 mini, and 4.1 nano.
- Multimodal (accepts text and images)
- Massive 1 million-token context window (~750,000 words)
- Significantly improved coding performance (e.g. 54.6% on a software engineering benchmark)
GPT-4.1 is not available in the standard ChatGPT app but is accessible through OpenAI’s API, which means it’s geared towards developers, companies, and AI enthusiasts. However, you can use GPT 4.1 on Overchat AI through our chatbot widgets.
GPT-4o
GPT-4o (often read as “GPT-4-oh”) is an optimized version of GPT-4, released in mid-2024. It became the core model used in ChatGPT and was designed to be faster, more efficient, and broadly accessible.
- Real-time performance with faster response speed
- Fully multimodal: supports text, images, and audio (used in ChatGPT’s voice and vision features)
- Improved multilingual capabilities and more recent knowledge (cutoff into 2024)
GPT-4o, sometimes branded as GPT-4 Turbo, became the default model in ChatGPT and was widely deployed in tools and apps for general-purpose use. Think of it as GPT-4, but more practical for everyday interaction.
GPT-o1
GPT-o1 (also called OpenAI o1) marks a shift toward models focused on reasoning. Released in late 2024, it was designed to improve logical thinking and multi-step problem solving.
- Performs internal chain-of-thought reasoning before giving answers
- Outperforms GPT-4 on complex tasks like math problems and strategic planning
- First available as o1-preview, then fully rolled out to ChatGPT Plus and Enterprise users
OpenAI positioned GPT-o1 as part of a separate line from the main GPT-n series, focused on logic and deep reasoning. It’s selectable within ChatGPT as an “Advanced Reasoning” option and is also being used in GitHub Copilot and Microsoft products for tasks needing higher cognitive depth.
GPT-5 vs. the GPT-4 Family: What’s the Difference?
With GPT-5 now being the current flagship, it’s useful to understand how it compares to the GPT-4 family (GPT-4, GPT-4o, GPT-4.5, GPT-4.1) that powered ChatGPT for the previous two years:
- GPT-5 has reasoning built in. Where GPT-4o had to be paired with a separate “o” model for hard problems, GPT-5 decides on its own when to think longer for a harder question.
- GPT-5 hallucinates dramatically less. OpenAI reports GPT-5 cuts factual errors by roughly half compared to GPT-4o on real-world questions.
- GPT-5 is the default in ChatGPT. The free tier gets a lightweight GPT-5 mini with daily limits, while paid tiers get the full GPT-5 family (GPT-5, GPT-5.1, GPT-5.2).
- Older GPT-4 models are still available via the API for backward compatibility, but most production traffic has shifted to GPT-5.
If you’re building something new, default to GPT-5. The older GPT-4 line is still useful if you have prompts that were tuned to its quirks, but for fresh work GPT-5 is both cheaper and stronger on almost every benchmark.
How to Try GPT for Yourself
There are many ways to access GPT technology. Some of the most popular options are:
- Overchat AI: Overchat AI is a multi-model chatbot app that lets you interact with various AI systems. Naturally, this includes the latest GPT-5, GPT-5.1, and GPT-5.2. It’s available on web and mobile and you can easily switch between models to compare them and choose the best one for your needs.
- Writing and content tools: Jasper uses GPT to help create blog posts, Grammarly improves tone and clarity, and Notion AI integrates GPT to summarize notes or generate content inside your workspace. Microsoft Word and Outlook also have GPT-powered tools, via Microsoft 365 Copilot, for drafting emails and documents.
- ChatGPT (OpenAI’s Consumer Chatbot). The free tier uses GPT-5 mini with daily message limits, while the ChatGPT Plus subscription ($20/month) grants access to the full GPT-5 family and higher caps. For unlimited access to the latest GPT-5 models we recommend using Overchat AI.
- OpenAI Playground. An interactive web tool for developers and power users. You can test prompts with adjustable settings, like temperature, max tokens and others. It requires an OpenAI API account, which is paid and often even more expensive than a website subscription.
Alternatives to GPT
Many AI systems compete with the original GPT. Here’s a brief look at some of the biggest ChatGPT alternatives:
- Claude vs GPT-5: Anthropic’s Claude Opus 4.7 is the closest direct competitor — bigger context window, very conversational, and often preferred for long-form writing and code review. GPT-5 still tends to win on raw reasoning benchmarks, but the gap is narrow.
- Gemini vs GPT-5: Gemini 3 Pro is Google’s current flagship and a serious contender, especially in coding and multimodality. Being from Google, it integrates search, maps, and other rich-content tools more natively.
- Llama vs GPT-5: Llama 4 is weaker than GPT-5 but it’s open source and free to run locally — great for non-English work if fine-tuned, and for use cases where data privacy matters.
- Mistral vs GPT-5: Mistral’s smaller open-weight models are much weaker than GPT-5 (due to size), but impressive for their footprint. Best for running on your own hardware where GPT-5 isn’t an option.
In addition to these models, there is a growing range of Chinese open-source models. Most famously DeepSeek V3.2 & R1 and Qwen3, plus newer models like Kimi K2 and GLM, which compete with GPT-5 in deep reasoning, coding, and logic — often at a fraction of the cost.
Bottom Line
GPT is a type of AI model that generates human-like text by predicting patterns in language. It’s the underlying technology behind many chatbots and writing tools, including ChatGPT, Microsoft Copilot, and Notion AI.
It’s used for tasks like answering questions, writing content, summarizing text, and assisting with code. To try it out for yourself and chat with GPT and other models like Claude or Gemini, start a free chat on Overchat AI.